Overview

Brought to you by YData

Dataset statistics

Number of variables12
Number of observations2773
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory281.6 KiB
Average record size in memory104.0 B

Variable types

Numeric12

Alerts

avg_basket_size is highly overall correlated with gross_revenue and 1 other fieldsHigh correlation
avg_recency_days is highly overall correlated with frequencyHigh correlation
avg_ticket is highly overall correlated with avg_unique_basket_sizeHigh correlation
avg_unique_basket_size is highly overall correlated with avg_ticket and 1 other fieldsHigh correlation
frequency is highly overall correlated with avg_recency_daysHigh correlation
gross_revenue is highly overall correlated with avg_basket_size and 3 other fieldsHigh correlation
qtde_produtcs is highly overall correlated with avg_unique_basket_size and 3 other fieldsHigh correlation
qte_invoices is highly overall correlated with gross_revenue and 2 other fieldsHigh correlation
qte_items is highly overall correlated with avg_basket_size and 3 other fieldsHigh correlation
avg_ticket is highly skewed (γ1 = 27.67827335) Skewed
frequency is highly skewed (γ1 = 46.07740946) Skewed
qtde_returns is highly skewed (γ1 = 21.6260127) Skewed
customer_id has unique values Unique
recency_days has 33 (1.2%) zeros Zeros
qtde_returns has 1481 (53.4%) zeros Zeros

Reproduction

Analysis started2025-04-09 19:32:53.176116
Analysis finished2025-04-09 19:33:28.920183
Duration35.74 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

customer_id
Real number (ℝ)

Unique 

Distinct2773
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15285.281
Minimum12347
Maximum18287
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2025-04-09T16:33:29.128572image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum12347
5-th percentile12626.6
Q113815
median15241
Q316780
95-th percentile17950.4
Maximum18287
Range5940
Interquartile range (IQR)2965

Descriptive statistics

Standard deviation1715.1526
Coefficient of variation (CV)0.11220942
Kurtosis-1.2070293
Mean15285.281
Median Absolute Deviation (MAD)1484
Skewness0.016612507
Sum42386085
Variance2941748.4
MonotonicityNot monotonic
2025-04-09T16:33:29.454065image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17850 1
 
< 0.1%
14482 1
 
< 0.1%
17058 1
 
< 0.1%
17704 1
 
< 0.1%
16933 1
 
< 0.1%
13772 1
 
< 0.1%
16249 1
 
< 0.1%
14198 1
 
< 0.1%
13989 1
 
< 0.1%
17930 1
 
< 0.1%
Other values (2763) 2763
99.6%
ValueCountFrequency (%)
12347 1
< 0.1%
12348 1
< 0.1%
12352 1
< 0.1%
12356 1
< 0.1%
12358 1
< 0.1%
12359 1
< 0.1%
12360 1
< 0.1%
12362 1
< 0.1%
12364 1
< 0.1%
12370 1
< 0.1%
ValueCountFrequency (%)
18287 1
< 0.1%
18283 1
< 0.1%
18282 1
< 0.1%
18273 1
< 0.1%
18272 1
< 0.1%
18270 1
< 0.1%
18265 1
< 0.1%
18263 1
< 0.1%
18261 1
< 0.1%
18260 1
< 0.1%

gross_revenue
Real number (ℝ)

High correlation 

Distinct2759
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2844.942
Minimum36.56
Maximum279138.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2025-04-09T16:33:29.755922image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum36.56
5-th percentile264.548
Q1628
median1169.94
Q32423.32
95-th percentile7490.982
Maximum279138.02
Range279101.46
Interquartile range (IQR)1795.32

Descriptive statistics

Standard deviation10466.686
Coefficient of variation (CV)3.6790506
Kurtosis372.80205
Mean2844.942
Median Absolute Deviation (MAD)689.02
Skewness17.097705
Sum7889024.2
Variance1.0955151 × 108
MonotonicityNot monotonic
2025-04-09T16:33:30.117085image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1025.44 2
 
0.1%
745.06 2
 
0.1%
889.93 2
 
0.1%
734.94 2
 
0.1%
331 2
 
0.1%
1314.45 2
 
0.1%
379.65 2
 
0.1%
1353.74 2
 
0.1%
598.2 2
 
0.1%
1078.96 2
 
0.1%
Other values (2749) 2753
99.3%
ValueCountFrequency (%)
36.56 1
< 0.1%
52 1
< 0.1%
52.2 1
< 0.1%
62.43 1
< 0.1%
68.84 1
< 0.1%
70.02 1
< 0.1%
77.4 1
< 0.1%
84.65 1
< 0.1%
90.3 1
< 0.1%
93.35 1
< 0.1%
ValueCountFrequency (%)
279138.02 1
< 0.1%
259657.3 1
< 0.1%
194550.79 1
< 0.1%
140438.72 1
< 0.1%
124564.53 1
< 0.1%
117375.63 1
< 0.1%
91062.38 1
< 0.1%
72882.09 1
< 0.1%
66653.56 1
< 0.1%
65019.62 1
< 0.1%

recency_days
Real number (ℝ)

Zeros 

Distinct252
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56.648395
Minimum0
Maximum372
Zeros33
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2025-04-09T16:33:30.426332image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q110
median29
Q373
95-th percentile211
Maximum372
Range372
Interquartile range (IQR)63

Descriptive statistics

Standard deviation68.422907
Coefficient of variation (CV)1.2078525
Kurtosis3.4305436
Mean56.648395
Median Absolute Deviation (MAD)23
Skewness1.8980349
Sum157086
Variance4681.6942
MonotonicityNot monotonic
2025-04-09T16:33:30.748507image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 99
 
3.6%
4 87
 
3.1%
2 85
 
3.1%
3 85
 
3.1%
8 76
 
2.7%
10 67
 
2.4%
9 66
 
2.4%
7 65
 
2.3%
17 62
 
2.2%
22 55
 
2.0%
Other values (242) 2026
73.1%
ValueCountFrequency (%)
0 33
 
1.2%
1 99
3.6%
2 85
3.1%
3 85
3.1%
4 87
3.1%
5 43
1.6%
7 65
2.3%
8 76
2.7%
9 66
2.4%
10 67
2.4%
ValueCountFrequency (%)
372 1
 
< 0.1%
366 1
 
< 0.1%
360 1
 
< 0.1%
358 3
0.1%
354 1
 
< 0.1%
337 1
 
< 0.1%
336 2
0.1%
334 1
 
< 0.1%
333 2
0.1%
330 1
 
< 0.1%

qte_invoices
Real number (ℝ)

High correlation 

Distinct55
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0544537
Minimum2
Maximum206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2025-04-09T16:33:31.069685image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q12
median4
Q36
95-th percentile17
Maximum206
Range204
Interquartile range (IQR)4

Descriptive statistics

Standard deviation9.0729125
Coefficient of variation (CV)1.4985518
Kurtosis183.89793
Mean6.0544537
Median Absolute Deviation (MAD)2
Skewness10.623447
Sum16789
Variance82.317741
MonotonicityNot monotonic
2025-04-09T16:33:31.408960image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 780
28.1%
3 498
18.0%
4 393
14.2%
5 237
 
8.5%
6 173
 
6.2%
7 138
 
5.0%
8 98
 
3.5%
9 69
 
2.5%
10 55
 
2.0%
11 54
 
1.9%
Other values (45) 278
 
10.0%
ValueCountFrequency (%)
2 780
28.1%
3 498
18.0%
4 393
14.2%
5 237
 
8.5%
6 173
 
6.2%
7 138
 
5.0%
8 98
 
3.5%
9 69
 
2.5%
10 55
 
2.0%
11 54
 
1.9%
ValueCountFrequency (%)
206 1
< 0.1%
199 1
< 0.1%
124 1
< 0.1%
97 1
< 0.1%
91 2
0.1%
86 1
< 0.1%
72 1
< 0.1%
62 2
0.1%
60 1
< 0.1%
57 1
< 0.1%

qte_items
Real number (ℝ)

High correlation 

Distinct1631
Distinct (%)58.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1669.2236
Minimum2
Maximum196844
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2025-04-09T16:33:31.731543image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile119
Q1330
median699
Q31478
95-th percentile4614
Maximum196844
Range196842
Interquartile range (IQR)1148

Descriptive statistics

Standard deviation5885.8021
Coefficient of variation (CV)3.5260717
Kurtosis486.75708
Mean1669.2236
Median Absolute Deviation (MAD)449
Skewness18.198824
Sum4628757
Variance34642666
MonotonicityNot monotonic
2025-04-09T16:33:32.080488image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
310 11
 
0.4%
150 8
 
0.3%
246 8
 
0.3%
516 7
 
0.3%
1200 7
 
0.3%
200 7
 
0.3%
272 7
 
0.3%
219 7
 
0.3%
260 7
 
0.3%
300 7
 
0.3%
Other values (1621) 2697
97.3%
ValueCountFrequency (%)
2 1
< 0.1%
16 1
< 0.1%
17 1
< 0.1%
19 1
< 0.1%
20 1
< 0.1%
25 1
< 0.1%
27 2
0.1%
30 1
< 0.1%
32 1
< 0.1%
33 2
0.1%
ValueCountFrequency (%)
196844 1
< 0.1%
79963 1
< 0.1%
77373 1
< 0.1%
69993 1
< 0.1%
64549 1
< 0.1%
64124 1
< 0.1%
62812 1
< 0.1%
58243 1
< 0.1%
57785 1
< 0.1%
50255 1
< 0.1%

qtde_produtcs
Real number (ℝ)

High correlation 

Distinct468
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.76884
Minimum2
Maximum7837
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2025-04-09T16:33:32.414183image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile10
Q134
median72
Q3143
95-th percentile400.2
Maximum7837
Range7835
Interquartile range (IQR)109

Descriptive statistics

Standard deviation277.76899
Coefficient of variation (CV)2.1404907
Kurtosis336.71947
Mean129.76884
Median Absolute Deviation (MAD)45
Skewness15.345709
Sum359849
Variance77155.614
MonotonicityNot monotonic
2025-04-09T16:33:32.742308image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28 40
 
1.4%
35 34
 
1.2%
27 30
 
1.1%
26 30
 
1.1%
29 28
 
1.0%
31 27
 
1.0%
15 27
 
1.0%
33 27
 
1.0%
25 26
 
0.9%
42 26
 
0.9%
Other values (458) 2478
89.4%
ValueCountFrequency (%)
2 11
0.4%
3 12
0.4%
4 16
0.6%
5 16
0.6%
6 24
0.9%
7 14
0.5%
8 13
0.5%
9 20
0.7%
10 18
0.6%
11 23
0.8%
ValueCountFrequency (%)
7837 1
< 0.1%
5670 1
< 0.1%
5095 1
< 0.1%
4577 1
< 0.1%
2698 1
< 0.1%
2379 1
< 0.1%
2060 1
< 0.1%
1818 1
< 0.1%
1673 1
< 0.1%
1636 1
< 0.1%

avg_ticket
Real number (ℝ)

High correlation  Skewed 

Distinct2771
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.106572
Minimum2.1505882
Maximum4453.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2025-04-09T16:33:33.064936image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum2.1505882
5-th percentile4.8524538
Q112.41668
median17.943444
Q325.025556
95-th percentile87.757474
Maximum4453.43
Range4451.2794
Interquartile range (IQR)12.608876

Descriptive statistics

Standard deviation107.63141
Coefficient of variation (CV)3.3523171
Kurtosis1054.6276
Mean32.106572
Median Absolute Deviation (MAD)6.3346556
Skewness27.678273
Sum89031.523
Variance11584.52
MonotonicityNot monotonic
2025-04-09T16:33:33.387244image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14.47833333 2
 
0.1%
4.162 2
 
0.1%
25.6761194 1
 
< 0.1%
44.95564103 1
 
< 0.1%
32.59775 1
 
< 0.1%
19.03048387 1
 
< 0.1%
28.55451613 1
 
< 0.1%
12.80068182 1
 
< 0.1%
6.396214689 1
 
< 0.1%
26.08797101 1
 
< 0.1%
Other values (2761) 2761
99.6%
ValueCountFrequency (%)
2.150588235 1
< 0.1%
2.4325 1
< 0.1%
2.462371134 1
< 0.1%
2.511241379 1
< 0.1%
2.515333333 1
< 0.1%
2.65 1
< 0.1%
2.656931818 1
< 0.1%
2.707598253 1
< 0.1%
2.760621572 1
< 0.1%
2.770464191 1
< 0.1%
ValueCountFrequency (%)
4453.43 1
< 0.1%
1687.2 1
< 0.1%
952.9875 1
< 0.1%
872.13 1
< 0.1%
841.0214493 1
< 0.1%
651.1683333 1
< 0.1%
640 1
< 0.1%
624.4 1
< 0.1%
615.75 1
< 0.1%
602.4531323 1
< 0.1%

avg_recency_days
Real number (ℝ)

High correlation 

Distinct1155
Distinct (%)41.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78.756379
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2025-04-09T16:33:33.693511image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13
Q134.222222
median59
Q399
95-th percentile224
Maximum366
Range365
Interquartile range (IQR)64.777778

Descriptive statistics

Standard deviation66.483798
Coefficient of variation (CV)0.84417032
Kurtosis3.6897278
Mean78.756379
Median Absolute Deviation (MAD)30
Skewness1.8311845
Sum218391.44
Variance4420.0954
MonotonicityNot monotonic
2025-04-09T16:33:34.033503image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
70 21
 
0.8%
46 18
 
0.6%
55 17
 
0.6%
49 16
 
0.6%
31 16
 
0.6%
91 16
 
0.6%
21 15
 
0.5%
35 15
 
0.5%
42 15
 
0.5%
28 14
 
0.5%
Other values (1145) 2610
94.1%
ValueCountFrequency (%)
1 9
0.3%
2 4
0.1%
2.861538462 1
 
< 0.1%
3 6
0.2%
3.330357143 1
 
< 0.1%
3.351351351 1
 
< 0.1%
4 5
0.2%
4.191011236 1
 
< 0.1%
4.275862069 1
 
< 0.1%
4.5 1
 
< 0.1%
ValueCountFrequency (%)
366 1
 
< 0.1%
365 1
 
< 0.1%
364 1
 
< 0.1%
363 1
 
< 0.1%
357 2
0.1%
356 1
 
< 0.1%
355 2
0.1%
352 1
 
< 0.1%
351 2
0.1%
350 3
0.1%

frequency
Real number (ℝ)

High correlation  Skewed 

Distinct1225
Distinct (%)44.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.049706611
Minimum0.0054495913
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2025-04-09T16:33:34.361597image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0.0054495913
5-th percentile0.0087463557
Q10.015789474
median0.024390244
Q30.041666667
95-th percentile0.11538462
Maximum17
Range16.99455
Interquartile range (IQR)0.025877193

Descriptive statistics

Standard deviation0.33765504
Coefficient of variation (CV)6.7929604
Kurtosis2295.7098
Mean0.049706611
Median Absolute Deviation (MAD)0.010691614
Skewness46.077409
Sum137.83643
Variance0.11401092
MonotonicityNot monotonic
2025-04-09T16:33:34.687173image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0625 17
 
0.6%
0.02777777778 17
 
0.6%
0.02380952381 16
 
0.6%
0.08333333333 15
 
0.5%
0.09090909091 15
 
0.5%
0.03448275862 14
 
0.5%
0.02941176471 14
 
0.5%
0.07692307692 13
 
0.5%
0.02127659574 13
 
0.5%
0.02564102564 13
 
0.5%
Other values (1215) 2626
94.7%
ValueCountFrequency (%)
0.005449591281 1
 
< 0.1%
0.005464480874 1
 
< 0.1%
0.005479452055 1
 
< 0.1%
0.005494505495 1
 
< 0.1%
0.005586592179 2
0.1%
0.005602240896 1
 
< 0.1%
0.005617977528 2
0.1%
0.00566572238 1
 
< 0.1%
0.005681818182 2
0.1%
0.005698005698 3
0.1%
ValueCountFrequency (%)
17 1
 
< 0.1%
3 1
 
< 0.1%
2 1
 
< 0.1%
1.142857143 1
 
< 0.1%
1 8
0.3%
0.75 1
 
< 0.1%
0.6666666667 3
 
0.1%
0.550802139 1
 
< 0.1%
0.5335120643 1
 
< 0.1%
0.5 3
 
0.1%

qtde_returns
Real number (ℝ)

Skewed  Zeros 

Distinct204
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.973675
Minimum0
Maximum9014
Zeros1481
Zeros (%)53.4%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2025-04-09T16:33:35.013940image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q39
95-th percentile96.8
Maximum9014
Range9014
Interquartile range (IQR)9

Descriptive statistics

Standard deviation290.71429
Coefficient of variation (CV)8.3123747
Kurtosis571.74568
Mean34.973675
Median Absolute Deviation (MAD)0
Skewness21.626013
Sum96982
Variance84514.798
MonotonicityNot monotonic
2025-04-09T16:33:35.330510image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1481
53.4%
1 129
 
4.7%
2 117
 
4.2%
3 82
 
3.0%
4 72
 
2.6%
6 63
 
2.3%
5 55
 
2.0%
12 45
 
1.6%
8 39
 
1.4%
9 38
 
1.4%
Other values (194) 652
23.5%
ValueCountFrequency (%)
0 1481
53.4%
1 129
 
4.7%
2 117
 
4.2%
3 82
 
3.0%
4 72
 
2.6%
5 55
 
2.0%
6 63
 
2.3%
7 38
 
1.4%
8 39
 
1.4%
9 38
 
1.4%
ValueCountFrequency (%)
9014 1
< 0.1%
8004 1
< 0.1%
4427 1
< 0.1%
3768 1
< 0.1%
3332 1
< 0.1%
2878 1
< 0.1%
2022 1
< 0.1%
2012 1
< 0.1%
1776 1
< 0.1%
1594 1
< 0.1%

avg_basket_size
Real number (ℝ)

High correlation 

Distinct1931
Distinct (%)69.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean230.94908
Minimum1
Maximum6009.3333
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2025-04-09T16:33:35.630764image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile45
Q1103.33333
median172
Q3278.09524
95-th percentile583.6
Maximum6009.3333
Range6008.3333
Interquartile range (IQR)174.7619

Descriptive statistics

Standard deviation261.5335
Coefficient of variation (CV)1.1324293
Kurtosis115.89887
Mean230.94908
Median Absolute Deviation (MAD)81
Skewness7.7349287
Sum640421.79
Variance68399.773
MonotonicityNot monotonic
2025-04-09T16:33:35.950793image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 11
 
0.4%
86 9
 
0.3%
60 8
 
0.3%
75 8
 
0.3%
197 7
 
0.3%
73 7
 
0.3%
82 7
 
0.3%
136 7
 
0.3%
105 7
 
0.3%
208 7
 
0.3%
Other values (1921) 2695
97.2%
ValueCountFrequency (%)
1 1
< 0.1%
3.333333333 1
< 0.1%
5.333333333 1
< 0.1%
5.666666667 1
< 0.1%
6.142857143 1
< 0.1%
7.5 1
< 0.1%
9 1
< 0.1%
9.5 1
< 0.1%
11 1
< 0.1%
11.875 1
< 0.1%
ValueCountFrequency (%)
6009.333333 1
< 0.1%
3868.65 1
< 0.1%
2880 1
< 0.1%
2733.944444 1
< 0.1%
2518.769231 1
< 0.1%
2160.333333 1
< 0.1%
2082.225806 1
< 0.1%
2000 1
< 0.1%
1903.5 1
< 0.1%
1866.933333 1
< 0.1%

avg_unique_basket_size
Real number (ℝ)

High correlation 

Distinct902
Distinct (%)32.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.141537
Minimum0.2
Maximum177
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size43.3 KiB
2025-04-09T16:33:36.264920image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile2
Q17.5454545
median13.5
Q322
95-th percentile45.1
Maximum177
Range176.8
Interquartile range (IQR)14.454545

Descriptive statistics

Standard deviation14.265048
Coefficient of variation (CV)0.8321919
Kurtosis9.9923133
Mean17.141537
Median Absolute Deviation (MAD)6.6666667
Skewness2.2443707
Sum47533.482
Variance203.4916
MonotonicityNot monotonic
2025-04-09T16:33:36.587895image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 34
 
1.2%
16 34
 
1.2%
13 34
 
1.2%
9 33
 
1.2%
7 32
 
1.2%
12 30
 
1.1%
18.5 29
 
1.0%
6 29
 
1.0%
14 28
 
1.0%
17 28
 
1.0%
Other values (892) 2462
88.8%
ValueCountFrequency (%)
0.2 1
 
< 0.1%
0.25 3
 
0.1%
0.3333333333 6
0.2%
0.4 1
 
< 0.1%
0.4090909091 1
 
< 0.1%
0.5 12
0.4%
0.5454545455 1
 
< 0.1%
0.5555555556 1
 
< 0.1%
0.5714285714 1
 
< 0.1%
0.6176470588 1
 
< 0.1%
ValueCountFrequency (%)
177 1
< 0.1%
105 1
< 0.1%
104 1
< 0.1%
98 1
< 0.1%
95.5 1
< 0.1%
94.33333333 1
< 0.1%
93 1
< 0.1%
89.625 1
< 0.1%
87 1
< 0.1%
85.66666667 1
< 0.1%

Interactions

2025-04-09T16:33:25.461188image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:32:53.669452image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:32:56.702753image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:32:59.742416image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:02.900442image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:06.047925image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:08.887298image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:11.736147image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:14.409704image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:17.203152image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:20.037414image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:22.692804image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:25.686489image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:32:53.934412image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:32:56.960923image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:32:59.996362image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:03.153896image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:06.276360image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:09.120607image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:11.952267image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:14.640896image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:17.433435image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:20.250387image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:22.914315image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:25.916258image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:32:54.171031image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:32:57.198994image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:00.247901image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:03.423151image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:06.501604image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:09.345942image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:12.171721image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:14.862810image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:17.659282image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:20.459280image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:23.131697image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:26.152898image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:32:54.422992image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:32:57.440806image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:00.516507image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:03.688844image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:06.752147image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:09.585428image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:12.402172image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:15.096881image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:17.904823image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:20.682838image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:23.366045image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:26.401151image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:32:54.694327image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:32:57.704986image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:00.781644image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:04.002687image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:06.995509image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:09.839942image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:12.634032image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:15.341783image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:18.154138image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:20.914984image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:23.611580image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:26.649735image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:32:54.983556image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:32:57.965461image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:01.058027image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:04.281323image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:07.242556image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:10.089272image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:12.876264image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:15.592134image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:18.400615image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:21.147648image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:23.856187image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:26.896673image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:32:55.244602image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:32:58.221691image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:01.331422image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:04.569631image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:07.489866image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:10.339201image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:13.106899image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:15.842817image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:18.638697image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:21.382059image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:24.103191image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:27.104852image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:32:55.481337image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:32:58.447970image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:01.559110image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:04.817249image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:07.707259image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:10.558131image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:13.316900image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:16.052295image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:18.852792image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:21.585826image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:24.315843image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:27.341302image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:32:55.742694image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:32:58.699603image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:01.838198image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:05.060394image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:07.944143image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:10.799684image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:13.541892image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:16.289320image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:19.091316image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:21.819737image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:24.554882image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:27.586460image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:32:55.987423image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:32:58.949381image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:02.136811image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:05.295162image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:08.184705image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:11.045318image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:13.767079image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:16.530374image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:19.331596image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:22.040968image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:24.797322image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:27.804336image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:32:56.202448image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:32:59.172634image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:02.395498image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:05.531109image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:08.410171image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:11.262923image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:13.965091image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:16.746434image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:19.556884image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:22.247095image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:25.005061image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:28.042678image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:32:56.448861image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:32:59.469575image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:02.647124image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:05.800603image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:08.651167image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:11.494303image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:14.178742image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:16.974341image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:19.794016image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:22.460993image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-04-09T16:33:25.227943image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Correlations

2025-04-09T16:33:36.820311image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
avg_basket_sizeavg_recency_daysavg_ticketavg_unique_basket_sizecustomer_idfrequencygross_revenueqtde_produtcsqtde_returnsqte_invoicesqte_itemsrecency_days
avg_basket_size1.000-0.0430.1980.384-0.1210.0260.6020.4030.2140.1260.759-0.103
avg_recency_days-0.0431.000-0.0800.187-0.012-0.952-0.367-0.300-0.215-0.476-0.3440.225
avg_ticket0.198-0.0801.000-0.639-0.1410.0820.273-0.3810.1880.0910.1950.035
avg_unique_basket_size0.3840.187-0.6391.000-0.001-0.1660.1040.546-0.064-0.1800.1470.005
customer_id-0.121-0.012-0.141-0.0011.0000.014-0.0860.013-0.0580.013-0.0790.014
frequency0.026-0.9520.082-0.1660.0141.0000.2590.2010.1760.3220.240-0.127
gross_revenue0.602-0.3670.2730.104-0.0860.2591.0000.7230.4610.7630.922-0.373
qtde_produtcs0.403-0.300-0.3810.5460.0130.2010.7231.0000.3290.6590.709-0.392
qtde_returns0.214-0.2150.188-0.064-0.0580.1760.4610.3291.0000.4270.426-0.186
qte_invoices0.126-0.4760.091-0.1800.0130.3220.7630.6590.4271.0000.704-0.448
qte_items0.759-0.3440.1950.147-0.0790.2400.9220.7090.4260.7041.000-0.365
recency_days-0.1030.2250.0350.0050.014-0.127-0.373-0.392-0.186-0.448-0.3651.000

Missing values

2025-04-09T16:33:28.378402image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
A simple visualization of nullity by column.
2025-04-09T16:33:28.763414image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

customer_idgross_revenuerecency_daysqte_invoicesqte_itemsqtde_produtcsavg_ticketavg_recency_daysfrequencyqtde_returnsavg_basket_sizeavg_unique_basket_size
0178505391.21372.034.01733.0297.018.1522221.00000017.00000040.050.9705880.617647
1130473232.5956.09.01390.0171.018.90403552.8333330.02830235.0154.44444411.666667
2125836705.382.015.05028.0232.028.90250026.5000000.04032350.0335.2000007.600000
313748948.2595.05.0439.028.033.86607192.6666670.0179210.087.8000004.800000
415100876.00333.03.080.03.0292.00000020.0000000.07317122.026.6666670.333333
5152914623.3025.014.02102.0102.045.32647126.7692310.04011529.0150.1428574.357143
6146885630.877.021.03621.0327.017.21978619.2631580.057221399.0172.4285717.047619
7178095411.9116.012.02057.061.088.71983639.6666670.03352041.0171.4166673.833333
81531160767.900.091.038194.02379.025.5434644.1910110.243316474.0419.7142866.230769
9160982005.6387.07.0613.067.029.93477647.6666670.0243900.087.5714294.857143
customer_idgross_revenuerecency_daysqte_invoicesqte_itemsqtde_produtcsavg_ticketavg_recency_daysfrequencyqtde_returnsavg_basket_sizeavg_unique_basket_size
561017290525.243.02.0404.0102.05.14941213.00.1428570.0202.00000046.000000
56191478577.4010.02.084.03.025.8000005.00.3333330.042.0000001.000000
562017254272.444.02.0252.0112.02.43250011.00.1666670.0126.00000050.000000
563617232421.522.02.0203.036.011.70888912.00.1538460.0101.50000015.000000
563717468137.0010.02.0116.05.027.4000004.00.4000000.058.0000002.500000
564813596697.045.02.0406.0166.04.1990367.00.2500000.0203.00000066.500000
5654148931237.859.02.0799.073.016.9568492.00.6666670.0399.50000036.000000
567914126706.137.03.0508.015.047.0753333.00.75000050.0169.3333334.666667
5685135211092.391.03.0733.0435.02.5112414.50.3000000.0244.333333104.000000
569515060301.848.04.0262.0120.02.5153331.02.0000000.065.50000020.000000